Implementing a data definition facility driven by graph grammars

The implementation of a data definition facility based on graph transformations is discussed. The theory of graph grammars allows a precise characterization of these transformations, facilitating proofs of correctness.The implementation consists of an extension to PL/I, and utilizes the standard PL/I preprocessor.     

Correct transformation: From object-based graph grammars to PROMELA

Model transformation is an approach that, among other advantages, enables the reuse of existing analysis and implementation techniques, languages and tools. The area of formal verification makes wide use of model transformation because the cost of constructing efficient model checkers is extremely high. There are various examples of translations from specification and programming languages to the input languages of prominent model checking tools, like SPIN. However, this approach provides a safe analysis method only if there is a guarantee that the transformation process preserves the semantics of the original specification/program, that is, that the transformation is correct. Depending on the source and/or target languages, this notion of correctness is not easy to achieve. In this paper, we tackle this problem in the context of Object-Based Graph Grammars (OBGG). OBGG is a formal language suitable for the specification of distributed systems, with a variety of tools and techniques centered around the transformation of OBGG models. We describe in details the model transformation from OBGG models to PROMELA, the input language of the SPIN model checker. Amongst the contributions of this paper are: (a) the correctness proof of the transformation from OBGG models to PROMELA; (b) a generalization of this process in steps that may be used as a guide to prove the correctness of transformations from different specification/programming languages to PROMELA.     

Propagation of constraints along model transformations using triple graph grammars and borrowed context

Fundamental properties of model transformations based on triple graph grammars (TGGs) have been studied extensively including syntactical correctness, completeness, termination and functional behavior. But up to now, it is an open problem how domain specific properties that are valid for a source model can be preserved along model transformations such that the transformed properties are valid for the derived target model. This question shows up in enterprise modeling. Here, modeling activities related to different domains are handled by different parties, and their models need to be consistent and integrated into one holistic enterprise model later on. So, support for decentralized modeling processes is needed. One technical aspect of the needed support in this case is the (bidirectional) propagation of constraints because that enables one party to understand and check the constraints of another party. Therefore, we analyze in the framework of TGGs how to propagate constraints from a source model to an integrated model and, afterwards, to a target model, such that, whenever the source model satisfies the source constraint, also the integrated and target model satisfy the corresponding integrated and target constraint. In our main new results we show under which conditions this is possible.     

Attribute grammars for scalable query processing on XML streams

We introduce the notion of XML Stream Attribute Grammars (XSAGs). XSAGs are the first scalable query language for XML streams (running strictly in linear time with bounded memory consumption independent of the size of the stream) that allows for actual data transformations rather than just document filtering. XSAGs are also relatively easy to use for humans. Moreover, the XSAG formalism provides a strong intuition for which queries can or cannot be processed scalably on streams. We introduce XSAGs together with the necessary language-theoretic machinery, study their theoretical properties such as expressiveness and complexity, and discuss their implementation.     

Feature grammars for semantic analysis

In this paper, we present a formalism called feature grammar and its application to several problems of semantic analysis. Our extension concerns the structure of the feature value sets, which can be complex, and the definition of unification, which is dependent on this structure. Moreover, we introduce generation rules for feature symbols in order to determine well-formed symbols, which form the alphabet of a formal language for natural language analysis.     

One-sided forbidding grammars and selective substitution grammars

In one-sided forbidding grammars, the set of rules is divided into the set of left forbidding rules and the set of right forbidding rules. A left forbidding rule can rewrite a non-terminal if each of its forbidding symbols is absent to the left of the rewritten symbol in the current sentential form, while a right forbidding rule is applied analogically except that this absence is verified to the right. Apart from this, they work like ordinary forbidding grammars. As its main result, this paper proves that one-sided forbidding grammars are equivalent to selective substitution grammars. This equivalence is established in terms of grammars with and without erasing rules. Furthermore, this paper proves that one-sided forbidding grammars in which the set of left forbidding rules coincides with the set of right forbidding rules characterize the family of context-free languages. In the conclusion, the significance of the achieved results is discussed.     

A CKY parser for picture grammars

We study the complexity of the membership or parsing problem for pictures generated by a family of picture grammars: Siromoney's Context-Free Kolam Array grammars (coincident with Matz's context-free picture grammars). We describe a new parsing algorithm, which extends the Cocke, Kasami and Younger's classical parsing technique for string languages and preserves the polynomial time complexity.     

Modelling and querying geographical data warehouses

A number of proposals for integrating geographical (Geographical Information Systems—GIS) and multidimensional (data warehouse—DW and online analytical processing—OLAP) processing are found in the database literature. However, most of the current approaches do not take into account the use of a GDW (geographical data warehouse) metamodel or query language to make available the simultaneous specification of multidimensional and spatial operators. To address this, this paper discusses the UML class diagram of a GDW metamodel and proposes its formal specifications. We then present a formal metamodel for a geographical data cube and propose the Geographical Multidimensional Query Language (GeoMDQL) as well. GeoMDQL is based on well-known standards such as the MultiDimensional eXpressions (MDX) language and OGC simple features specification for SQL and has been specifically defined for spatial OLAP environments based on a GDW. We also present the GeoMDQL syntax and a discussion regarding the taxonomy of GeoMDQL query types. Additionally, aspects related to the GeoMDQL architecture implementation are described, along with a case study involving the Brazilian public healthcare system in order to illustrate the proposed query language.     

Extending OCL for OLAP querying on conceptual multidimensional models of data warehouses

The development of data warehouses begins with the definition of multidimensional models at the conceptual level in order to structure data, which will facilitate decision makers with an easier data analysis. Current proposals for conceptual multidimensional modelling focus on the design of static data warehouse structures, but few approaches model the queries which the data warehouse should support by means of OLAP (on-line analytical processing) tools. OLAP queries are, therefore, only defined once the rest of the data warehouse has been implemented, which prevents designers from verifying from the very beginning of the development whether the decision maker will be able to obtain the required information from the data warehouse. This article presents a solution to this drawback consisting of an extension to the object constraint language (OCL), which has been developed to include a set of predefined OLAP operators. These operators can be used to define platform-independent OLAP queries as a part of the specification of the data warehouse conceptual multidimensional model. Furthermore, OLAP tools require the implementation of queries to assure performance optimisations based on pre-aggregation. It is interesting to note that the OLAP queries defined by our approach can be automatically implemented in the rest of the data warehouse, in a coherent and integrated manner. This implementation is supported by a code-generation architecture aligned with model-driven technologies, in particular the MDA (model-driven architecture) proposal. Finally, our proposal has been validated by means of a set of sample data sets from a well-known case study.     

Graph grammars with string-regulated rewriting

Multicellular organisms undergo a complex developmental process, orchestrated by the genetic information in their cells, in order to form a newborn individual from a fertilized egg. This complex process, not completely understood yet, is believed to have a key role in generating the impressive biotic diversity of organisms found on earth. Inspired by mechanisms of Eukaryotic genetic expression, we propose and analyse graph grammars with string-regulated rewriting. In these grammatical systems a genome sequence is represented by a regulatory string, a graph corresponds to an organism, and a set of graph grammar rules represents different forms of implementing cell division. Accordingly, a graph derivation by the graph grammar resembles the developmental process of an organism. We give examples of the concept and compare its generative power to the power of the traditional context-free graph grammars. We demonstrate that the power of expression increases when genetic regulation is included in the model, as compared to non-regulated grammars. Additionally, we propose a hierarchy of string-regulated graph grammars, arranged by expressive power. These results highlight the key role that the transmission of regulatory information during development has in the emergence of biological diversity.     

A graph grammar‐based approach for graph layout

As a two‐dimensional formal tool, graph grammars are capable of handling the layout problems of visual programming languages. Based on an edge‐based graph grammar (EGG), this paper proposes a novel layout approach that uses the unique features of EGG and overcomes the weakness of existing layout approaches. In order to make the approach rigorous yet concise, the graph grammar mechanisms with layout constraints and quantitative analysis techniques are combined together as an integrity. First, the basic notions of EGG are briefly introduced; second, the layout approach is presented that consists of two phases, ie, bottom‐up parsing and top‐down derivation. Finally, a case study is given by taking the standard flowchart as an example to demonstrate the working process of the proposed approach.     

A unified framework for heterogeneous patterns

Knowledge patterns, such as association rules, clusters or decision trees, can be defined as concise and relevant information that can be extracted, stored, analyzed, and manipulated by knowledge workers in order to drive and specialize business decision processes. In this paper we deal with data mining patterns. The ability to manipulate different types of patterns under a unified environment is becoming a fundamental issue for any ‘intelligent’ and data-intensive application. However, approaches proposed so far for pattern management usually deal with specific and predefined types of patterns and mainly concern pattern extraction and exchange issues. Issues concerning the integrated, advanced management of heterogeneous patterns are in general not (or marginally) taken into account.     

基于概念图的信息检索的查询扩展模型

针对传统的基于关键词匹配的信息检索存在的查全率和精确率不高的问题,提出一种基于概念图匹配的查询扩展方法：一方面通过知网对用户查询的词或者句子进行扩展后,将用户查询和文档生成概念图;另一方面利用概念图的不完全匹配和语义相似度的计算方法计算概念图的相似度,以提高检索效果。实验结果表明该方法取得了良好的效果。     

Inference for transition network grammars

This paper gives a brief introduction to transition networks and proposes an approach to the inference of transition network grammars.     

A linear time algorithm for monadic querying of indefinite data over linearly ordered domains

This paper demonstrates the generation of a linear-time query-answering algorithm based on the constructive proof of Higman’s lemma by Murthy and Russell [Proceedings of the 5th IEEE Symposium on Logic in Computer Science, 1990, p. 257–267]. The target problem is linear-time evaluation of a fixed disjunctive monadic query on an indefinite database over linearly ordered domains, first posed by van der Meyden [Proceedings of the 11th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 1992, p. 331–345]. Van der Meyden showed the existence of a linear-time algorithm, but an explicit construction has, until now, not been reported.     

A probabilistic plan recognition algorithm based on plan tree grammars

We present the PHATT algorithm for plan recognition. Unlike previous approaches to plan recognition, PHATT is based on a model of plan execution. We show that this clarifies several difficult issues in plan recognition including the execution of multiple interleaved root goals, partially ordered plans, and failing to observe actions. We present the PHATT algorithm's theoretical basis, and an implementation based on tree structures. We also investigate the algorithm's complexity, both analytically and empirically. Finally, we present PHATT's integrated constraint reasoning for parametrized actions and temporal constraints.